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<p>This document is the API specification for the AWS AI toolkit for DJL.

<p>The aws-ai module contains classes that make it easy for DJL to access AWS services.

<p>You can use this toolkit to load models from AWS S3 bucket directly:

<pre>
    // Set model zoo search path system property. The value can be
    // comma delimited url string. You can add multiple s3 url.
    // The S3 url should point to a folder in your s3 bucket.
    // In current implementation, DJL will only download files directly
    // in that folder. The archive file like .zip, .tar.gz, .tgz, .tar.z
    // files will be extracted automatically. This is useful for the models
    // that are created by AWS SageMaker.
    // The folder name will be interpreted as artifactId and modelName.
    // If your model file has a different name then the folder name, you
    // need use query string to tell DJL which model you want to load.
    System.setProperty("ai.djl.repository.zoo.location",
            "s3://djl-misc/test/models/<b>resnet18</b>?model_name=<i>resent18_v1</i>");

    Criteria&lt;Image, Classifications&gt; criteria =
        Criteria.builder()
                .optApplication(Application.CV.IMAGE_CLASSIFICATION)
                .setTypes(Image.class, Classifications.class)
                .optArtifactId("ai.djl.localmodelzoo:<b>resnet18</b>")
                .optProgress(new ProgressBar())
                .build();

    ZooModel&lt;Image, Classifications&gt; model = criteria.loadModel();
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